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Retours d’expériences Big Data en entreprise CRAY - INSTITUTE FOR SYSTEMS BIOLOGY CRAY SOLUTION BRIEF | CANCER RESEARCH USING A BIG DATA APPROACH THE CHALLENGE Cancer researchers have a wealth of data available to them regarding the molecular and clinical characteristics of the many forms of cancers and the use of therapeutic drugs to treat disease. This data includes both proprietary research from their own labs as well as publicly available data such as The Cancer Genome Atlas and other collaborative scientific and public sources. The hypothesis is that big data could be used to identify potential new drug treatments from data already available through analysis of gene-drug relationships without performing “wet” lab work first. However, traditional analytics tools and techniques to test these hypotheses often take several weeks to months to execute. They are time consuming because data scientists must assemble all of the necessary data into a new data model to determine whether the researcher’s hypothesis is accurate. Because of the extensive amount of time between question and answer, the results of the experiment may be irrelevant by the time they are finally delivered. The researchers at the Institute for Systems Biology (ISB) wanted to determine whether they could significantly compress this wait time. They wanted a way to get to “yes” or “no” quickly in order to prioritize drug repurposing opportunities; this would then accelerate the discovery of new cancer treatments that could be moved through the drug development and approval process quickly, thus making a major difference to cancer patients. THE URIKA-GD PLATFORM ADVANTAGE: To rapidly validate scientific hypotheses in real time and discover new connections within their existing data, the ISB team needed a powerful solution that enabled data discovery at scale. THE SOLUTION The ISB team worked with Cray to develop an innovative, real-time approach to cancer research discovery using the Urika-GD graph analytics appliance. Using the Urika-GD system, the team was able to assemble all of its data into a single graph in the appliance’s vast shared memory — eliminating the need to partition the data or create time-consuming and complex data models prior to posing a hypothesis. This solution is scalable, which allows the data set to expand over time without losing performance or data integrity. The ISB team identified new cancer therapy candidates by exploring correlations between frequently mutated genes from tumor samples to identify existing gene-drug associations that could be possible drug candidates. In addition to discovering promising new therapies, they also sought to rapidly eliminate from consideration those drugs that would not deliver the desired result.. To deliver results quickly, the researchers needed a way to discover unknown relationships within the data that the current data management strategy couldn’t deliver. The Urika-GD system enabled ISB’s researchers to look at the data in a different way than what they’d be limited to with query-based relational database systems, where the data determines what questions can be asked. This resulted in a clear visualization of the connections and associations within the data to help identify promising candidates for new therapies. The graph analytics approach enabled the research team to identify thousands of drug repurposing opportunities that warranted further investigation. For example, this methodology revealed that nelfinavir, which is used to treat HIV, showed selectivity in a separate research study for HER2-breast cancer. The ISB team came to the same conclusion about nelfinavir in a fraction of the time, with no need for hands-on “wet lab” work to test the hypothesis - validating the accuracy and efficacy of the big data approach for identifying drug treatment solutions. THE URIKA-GD PLATFORM ADVANTAGE The Urika-GD system, with its large global shared memory, RDF/SPARQL interface and proprietary Threadstorm multithreaded graph processors, allowed the team to rapidly integrate ISB’s proprietary data with publicly available data, enabling the researchers to identify new relationships in the data without any upfront modeling. No advance knowledge of the relationships within the data is required to identify non-obvious patterns, facilitating true data discovery. Using the Urika-GD platform instead of traditional database strategies and investigative laboratory experiments, the ISB researchers significantly reduced the time to discovery, saving months or years of research with a higher probability of success. Document réalisé par la Société Corp Events - Janvier 2015 20
Retours d’expériences Big Data en entreprise SOLUTION BRIEF | CANCER RESEARCH The impact of using a more powerful analytics solution was immediate-and dramatic: In the amount of time it previously took to validate a single hypothesis, the team could now validate 1,000. About Urika-GD The Urika-GD big data appliance for graph analytics helps enterprises gain key insights by discovering relationships in big data. Its highly scalable, real-time graph analytics warehouse supports ad hoc queries, pattern-based searches, inferencing and deduction. The Urika-GD appliance complements an existing data warehouse or Hadoop® cluster by offloading graph workloads and interoperating within the existing analytics workflow. ABOUT CRAY GLOBAL SUPERCOMPUTING LEADER Cray Inc. provides innovative systems and solutions enabling scientists and engineers in industry, academia and government to meet existing and future simulation and analytics challenges. Leveraging more than 40 years of experience in developing and servicing the world’s most advanced supercomputers, Cray offers a comprehensive portfolio of supercomputers and big data storage and analytics solutions delivering unrivaled performance, efficiency and scalability. Go to www.cray.com for more information. ©2014 Cray Inc. All rights reserved. Specifications subject to change without notice. Cray is a registered trademark and Urika-GD is a trademark of Cray Inc. All other trademarks mentioned herein are the properties of their respective owners. 20140915 www.cray.com Document réalisé par la Société Corp Events - Janvier 2015 21
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